Rule-Based Mode Choice Model: INSIM Expert System
作者： Abdul Ahad Memon , Meng Meng , Yiik Diew Wong , Soi-Hoi Lam
DOI: 10.1061/(ASCE)TE.1943-5436.0000753
关键词: Statistical model 、 Traffic simulation 、 Adaptive learning 、 Discrete choice 、 Mode choice 、 Rule-based system 、 Expert system 、 Operations research 、 Mode (statistics) 、 Engineering
摘要: This paper presents an innovative rule-based intelligent network simulation model (INSIM) expert system (IES) which simulates real-time mode choice decision-making process of commuters in the presence multimodal traveler information. The IES captures interactions among available modes and decides on commuter’s based a socioeconomic traits prevailing travel condition. behavior is modeled represented by cognitive rules rule-base IES. Two important characteristics IES, reliability adaptive learning, are highlighted. Three different models, i.e., (1) pure (PRB), (2) discrete (DCM), (3) probabilistic (COM) introduced to formulate decisions. Simulation results show that highest level accuracy can be achieved applying PRB generate
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